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High-Precision Waveform Stacking Location Method for Microseismic Events Based on S-Transform.

Hongpeng Zhao^1,2, Jiulong Cheng^1,2, Grzegorz Lizurek³

¹College of Earth Science and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.

Sensors (Basel, Switzerland)

|November 27, 2025

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This study introduces a new method for microseismic source localization using the Stockwell transform (S-transform) to improve accuracy in noisy conditions. The enhanced technique offers superior noise resistance and precise event location for geotechnical engineering applications.

Area of Science:

Geophysics
Seismology
Signal Processing

Background:

Microseismic source localization is crucial in geotechnical engineering.
Traditional waveform stacking methods struggle with low signal-to-noise ratios (SNR).
Ambient noise and weak event energy degrade localization accuracy.

Purpose of the Study:

To enhance microseismic source localization precision and stability under low SNR conditions.
To develop a noise-resistant method for accurate event location.
To validate the proposed method using real seismic data.

Main Methods:

Utilized the Stockwell transform (S-transform) for time-frequency domain conversion.
Introduced frequency and time coefficients to enhance microseismic signal energy.

Keywords:

Stockwell transform characteristic functions frequency and time coefficients geotechnical engineering microseismic source localization

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Employed characteristic functions (CFs) computation and multiple-cross-correlation stacking for event location.

Main Results:

The S-transform-based method demonstrated superior noise resistance compared to STA/LTA and envelope methods.
Significantly improved localization accuracy was observed under varying noise levels.
The method effectively enhanced microseismic signal energy in the time-frequency domain.

Conclusions:

The proposed method enhances microseismic localization accuracy and stability in low SNR environments.
It offers a robust solution for geotechnical engineering applications.
Validated effectiveness using real coal mine seismic data.